We approximate the solution of a quasilinear stochastic partial differential equa- tion driven by fractional Brownian motion B_H(t); H in (0,1), which was calculated via fractional White Noise calculus, see [5].

To this day, terrorism perpetrated by non-state actors persists as a worldwide threat, as exemplified by the recent lethal attacks in Paris, London, Brussels, and the ongoing massacres perpetrated by the Islamic State in Iraq, Syria and neighbouring countries. In response, states deploy various counterterrorism policies, the costs of which could be reduced through more efficient preventive measures. The literature has not applied statistical models able to account for complex spatio-temporal dependencies, despite their potential for explaining and preventing non-state terrorism at the sub-national level. In an effort to address this shortcoming, this thesis employs Bayesian hierarchical models, where the spatial random field is represented by a stochastic partial differential equation. The results show that lethal terrorist attacks perpetrated by non-state actors tend to be concentrated in areas located within failed states from which they may diffuse locally, towards neighbouring areas. At the sub-national level, the propensity of attacks to be lethal and the frequency of lethal attacks appear to be driven by antagonistic mechanisms. Attacks are more likely to be lethal far away from large cities, at higher altitudes, in less economically developed areas, and in locations with higher ethnic diversity. In contrast, the frequency of lethal attacks tends to be higher in more economically developed areas, close to large cities, and within democratic countries.

We approximate the solution of a quasilinear stochastic partial differential equa- tion driven by fractional Brownian motion B_H(t); H in (0,1), which was calculated via fractional White Noise calculus, see [5].

Ces travaux présentent des avancées théoriques pour l'application de l'approche EDPS (Équation aux Dérivées Partielles Stochastique) en Géostatistique. On considère dans cette approche récente que les données régionalisées proviennent de la réalisation d'un Champ Aléatoire satisfaisant une EDPS. Dans le cadre théorique des Champs Aléatoires Généralisés, l'influence d'une EDPS linéaire sur la structure de covariance de ses éventuelles solutions a été étudiée avec une grande généralité. Un critère d'existence et d'unicité des solutions stationnaires pour une classe assez large d'EDPSs linéaires a été obtenu, ainsi que des expressions pour les mesures spectrales associées. Ces résultats permettent de développer des modèles spatio-temporels présentant des propriétés non-triviales grâce à l'analyse d'équations d'évolution présentant un ordre de dérivation temporel fractionnaire. Des paramétrisations adaptées de ces modèles permettent de contrôler leur séparabilité et leur symétrie ainsi que leur régularité spatiale et temporelle séparément. Des résultats concernant des solutions stationnaires pour des EDPSs issues de la physique telles que l'équation de la Chaleur et l'équation d'Onde sont présentés. Puis, une méthode de simulation non-conditionnelle adaptée à ces modèles est étudiée. Cette méthode est basée sur le calcul d'une approximation de la Transformée de Fourier du champ, et elle peut être implémentée de façon efficace grâce à la Transformée de Fourier Rapide. La convergence de cette méthode a été montrée théoriquement dans un sens faible et dans un sens fort. Cette méthode est appliquée à la résolution numérique des EDPSs présentées dans ces travaux. Des illustrations de modèles présentant des propriétés non-triviales et reliés à des équations de la physique sont alors présentées. / This dissertation presents theoretical advances in the application of the Stochastic Partial Differential Equation (SPDE) approach in Geostatistics. This recently developed approach consists in interpreting a regionalised data-set as a realisation of a Random Field satisfying a SPDE. Within the theoretical framework of Generalized Random Fields, the influence of a linear SPDE over the covariance structure of its potential solutions can be studied with a great generality. A criterion of existence and uniqueness of stationary solutions for a wide-class of linear SPDEs has been obtained, together with an expression for the related spectral measures. These results allow to develop spatio-temporal covariance models presenting non-trivial properties through the analysis of evolution equations presenting a fractional temporal derivative order. Suitable parametrizations of such models allow to control their separability, symmetry and separated space-time regularities. Results concerning stationary solutions for physically inspired SPDEs such as the Heat equation and the Wave equation are also presented. A method of non-conditional simulation adapted to these models is then studied. This method is based on the computation of an approximation of the Fourier Transform of the field, and it can be implemented efficiently thanks to the Fast Fourier Transform algorithm. The convergence of this method has been theoretically proven in suitable weak and strong senses. This method is applied to numerically solve the SPDEs studied in this work. Illustrations of models presenting non-trivial properties and related to physically driven equations are then given.

Motivated by a zero-intelligence approach, the aim of this thesis is to unify the microscopic (discrete price and volume), mesoscopic (discrete price and continuous volume) and macroscopic (continuous price and volume) frameworks of limit order books, with a view to providing a novel yet analytically tractable description of their behaviour in a high to ultra high-frequency setting. Starting with the canonical microscopic framework, the first part of the thesis examines the limiting behaviour of the order book process when order arrival and cancellation rates are sent to infinity and when volumes are considered to be of infinitesimal size. Mathematically speaking, this amounts to establishing the weak convergence of a discrete-space process to a mesoscopic diffusion limit. This step is initially carried out in a reduced-form context, in other words, by simply looking at the best bid and ask queues, before the procedure is extended to the whole book. This subsequently leads us to the second part of the thesis, which is devoted to the transition between mesoscopic and macroscopic models of limit order books, where the general idea is to send the tick size to zero, or equivalently, to consider infinitely many price levels. The macroscopic limit is then described in terms of reflected SPDEs which typically arise in stochastic interface models. Numerical applications are finally presented, notably via the simulation of the mesocopic and macroscopic limits, which can be used as market simulators for short-term price prediction or optimal execution strategies.

Diese Arbeit behandelt zwei Gebiete: stochastische partielle Rückwerts-Differentialgleichungen (BSPDEs) und Mean-Field-Games (MFGs). Im ersten Teil wird über eine stochastische Variante der De Giorgischen Iteration ein Maximumprinzip für quasilineare reflektierte BSPDEs (RBSPDEs) auf allgemeinen Gebieten bewiesen. Als Folgerung erhalten wir ein Maximumprinzip für RBSPDEs auf beschränkten, sowie für BSPDEs auf allgemeinen Gebieten. Abschließend wird das lokale Verhalten schwacher Lösungen untersucht. Im zweiten Teil zeigen wir zunächst die Existenz von Gleichgewichten in MFGs mit singulärer Kontrolle. Wir beweisen, dass die Lösung eines MFG ohne Endkosten und ohne Kosten in der singulären Kontrolle durch die Lösungen eines MFGs mit strikt regulären Kontrollen approximiert werden kann. Die vorgelegten Existenz- und Approximationsresultat basieren entscheidend auf der Wahl der Storokhod M1 Topologie auf dem Raum der Càdlàg-Funktion. Anschließend betrachten wir ein MFG optimaler Portfolioliquidierung unter asymmetrischer Information. Die Lösung des MFG charakterisieren wir über eine stochastische Vorwärts-Rückwärts-Differentialgleichung (FBSDE) mit singulärer Endbedingung der Rückwärtsgleichung oder alternativ über eine FBSDE mit endlicher Endbedingung, jedoch singulärem Treiber. Wir geben ein Fixpunktargument, um die Existenz und Eindeutigkeit einer Kurzzeitlösung in einem gewichteten Funktionenraum zu zeigen. Dies ermöglicht es, das ursprüngliche MFG mit entsprechenden MFGs ohne Zustandsendbedinung zu approximieren. Der zweite Teil wird abgeschlossen mit einem Leader-Follower-MFG mit Zustandsendbedingung im Kontext optimaler Portfolioliquidierung bei hierarchischer Agentenstruktur. Wir zeigen, dass das Problem beider Spielertypen auf singuläre FBSDEs zurückgeführt werden kann, welche mit ähnlichen Methoden wie im vorangegangen Abschnitt behandelt werden können. / The thesis is concerned with two topics: backward stochastic partial differential equations and mean filed games. In the first part, we establish a maximum principle for quasi-linear reflected backward stochastic partial differential equations (RBSPDEs) on a general domain by using a stochastic version of De Giorgi’s iteration. The maximum principle for RBSPDEs on a bounded domain and the maximum principle for BSPDEs on a general domain are obtained as byproducts. Finally, the local behavior of the weak solutions is considered. In the second part, we first establish the existence of equilibria to mean field games (MFGs) with singular controls. We also prove that the solutions to MFGs with no terminal cost and no cost from singular controls can be approximated by the solutions, respectively control rules, for MFGs with purely regular controls. Our existence and approximation results strongly hinge on the use of the Skorokhod M1 topology on the space of càdlàg functions. Subsequently, we consider an MFG of optimal portfolio liquidation under asymmetric information. We prove that the solution to the MFG can be characterized in terms of a forward backward stochastic differential equation (FBSDE) with possibly singular terminal condition on the backward component or, equivalently, in terms of an FBSDE with finite terminal value, yet singular driver. We apply the fixed point argument to prove the existence and uniqueness on a short time horizon in a weighted space. Our existence and uniqueness result allows to prove that our MFG can be approximated by a sequence of MFGs without state constraint. The final result of the second part is a leader follower MFG with terminal constraint arising from optimal portfolio liquidation between hierarchical agents. We show the problems for both follower and leader reduce to the solvability of singular FBSDEs, which can be solved by a modified approach of the previous result.